Everybody's talking about agents now and everybody's talking about loops. Loops, loops, loops everywhere. Loops have been around for a long time. Back in the '60s, people were debating who has the best programming language? Fortran or COBOL? No, mine is better. No, mine is better. Oh, you don't know anything. You don't know what you're talking about. Bohm and Jacopini in 1966 came out and said, "Okay, there is no real difference in programming languages if they have three aspects. Sequence. I can put statement A, statement B, statement C. Fine. I have conditionals. I can have if then. And the last piece, I have a loop. If I have a loop, if I have iteration, if I take these three things, the the language is what's called Turing complete. Can do any can compute anything that a can be computed by computational devices from the work of Alan Turing. Okay? And now we're seeing this in agentic AI. Agents are now have loops. Loops give us the last piece in the equation of giving us a technology that is capable of doing anything that computational devices can do. The danger though of loops is that they can break. If you're If you're a programmer, you know, you've all go into infinite loop. Not good. Loops can drift as agents start talking to each other, things get all go off off the rails. And loops can cost you money. Token counts crank up as the loops continue. So, you don't you need to be careful, okay? But in a way we are revisiting some of the early stuff with symbolic AI. I would argue we're going back to the world of expert systems. Which is the symbolic part of the whole